Number of Seats/Users: BigID offers discounts based on the number of users or seats. A higher volume typically leads to a better discount structure, especially for enterprise-level usage.

Commitment to a Long-Term Contract: Discounts are often provided to companies that commit to using the service for a longer period (e.g., 1-year or 3-year contracts). A longer commitment shows BigID that the company is serious and willing to invest in the platform long-term.

No Active Discounts: Companies that are not already receiving other active discounts may have a better chance of qualifying for additional discounts from BigID. BigID reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: BigID offers discounts if you agree to a minimum amount of usage or transaction volume. This could be based on data storage, transactions, or other metrics tied to how much you will use the platform.

Enterprise-Level Negotiation: Companies that qualify as “enterprise” due to their size or complexity (e.g., having large teams, multiple departments, or geographical presence) may be eligible for additional discounts from BigID. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: BigID often offers discounts if you renew early or prepay for the entire contract period. This is a common approach to securing a lower price.

Here at Spendbase our internal data shows that BigID is seen as a strong choice for companies that need serious data privacy, security, and governance – especially in regulated environments like GDPR.

From what Spendbase clients share with us, a few themes stand out:

What Spendbase clients like most

• Strong GDPR and privacy focus
• Clients say BigID “takes fear head on” when it comes to GDPR and cybersecurity.

• It helps non-technical teams understand complex privacy topics in a practical way.

• Deep data discovery and PII detection

• BigID is praised for scanning a wide range of data sources (Snowflake, S3, Hive, etc.).

• Our clients say it’s very effective at identifying PII and sensitive data across large data estates.

• Usability for both IT and business

• The interface is described as simple and user friendly, even for business users.

• This lowers the dependency on engineers for day-to-day data privacy tasks.

• Thought leadership and best practices

• Clients like that BigID “practices what they teach,” especially in how they handle consent and privacy flows.
• Many see it not just as a tool, but as a reference model for how to design their own privacy posture.

Common challenges and gaps

• Complexity of setup and concepts
• Our internal feedback shows that BigID is not a “plug-and-play” or “point-and-click” tool.

• Teams with little cybersecurity or privacy background typically need onboarding, training, or external help.

• Integration limitations

• One recurring point: missing or limited integration with some platforms like Databricks.
• This can create a partial view of data for companies heavily invested in those ecosystems.

Impact on cost and value (Spendbase perspective)

• BigID tends to deliver high value where:
• There is significant GDPR/CCPA or other regulatory pressure
• Organizations have many disparate data sources with unknown or poorly mapped PII

• Data privacy risk is directly tied to business or brand impact

• Cost-saving opportunities we usually look for:

• Matching license tiers to actual data sources in use
• Avoiding overlap with existing discovery/scanning tools
• Negotiating better terms around onboarding and support, since complexity is a known factor

In short, our internal data shows that BigID is a powerful, enterprise-grade data intelligence platform that shines in privacy and PII discovery, but it requires thoughtful implementation and careful contract structuring to get the best value.